Self-Propelled Sensor Rail for Plant Bed Monitoring
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Solution Overview
Problem
Large-scale indoor farming operations face challenges in efficiently monitoring environmental conditions and plant health due to the high cost of dedicated sensors and the impracticality of manual data collection across vertically stacked plant beds.
Innovation Solution
A self-propelled sensing system supported by a rail that moves along plant beds, equipped with sensors and a camera, collects data and images periodically and uploads them wirelessly, allowing for efficient monitoring of light, temperature, humidity, and plant health without obstructing plant growth.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If dedicated sensors are placed near each plant to monitor environmental conditions, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The sensing system is divided into multiple sensor pods that can be distributed along the plant bed. Each pod contains specific sensors (light, temperature, humidity, CO2) and can independently monitor local conditions, allowing precise measurement without requiring a single complex centralized system.
Solution Approach 2:
The sensor pods are designed to perform multiple functions - measuring light intensity, temperature, humidity, and CO2 levels simultaneously. This multi-functional approach reduces the need for separate dedicated sensors for each parameter, simplifying the overall system while maintaining comprehensive monitoring capability.
2Device complexity
If manual data collection is performed across vertically stacked plant beds, then device complexity is reduced, but productivity and time efficiency worsen
Solution Approach 1:
The sensing system is designed to be mobile rather than stationary. The self-propelled platform moves along rails above the plant beds, dynamically positioning sensors to collect data from multiple locations automatically. This eliminates the need for manual data collection while maintaining system simplicity.
Solution Approach 2:
The system performs data collection autonomously without requiring manual intervention. The self-propelled platform moves automatically along the rail, sensors continuously monitor environmental conditions, and data is uploaded wirelessly to the server, creating a self-service monitoring system that improves productivity.
3Measurement precision
If sensors are placed between vertically-stacked plant beds, then measurement precision is improved, but light availability to plants worsens
Solution Approach 1:
Instead of placing sensors vertically between plant beds where they would block light, the system moves the sensing platform to a horizontal dimension above the plants. The self-propelled platform travels along rails positioned overhead, allowing light to pass through to the plants unobstructed while sensors measure light intensity and other parameters from above.
Solution Approach 2:
The system uses an intermediary mobile platform that mediates between the need for accurate measurement and the need for unobstructed light. Rather than placing sensors directly in the light path between plants, the platform moves above the canopy, serving as an intermediary measurement point that doesn't interfere with plant lighting requirements.
4Productivity
If automated sensing systems are implemented to monitor all plant conditions, then productivity is improved, but device complexity and cost increase
Solution Approach 1:
The automated sensing system is segmented into modular sensor pods that can be independently deployed and configured. Each pod handles specific sensing functions, and multiple pods work together along the plant bed, reducing overall system complexity while maintaining comprehensive automated monitoring capability.
Solution Approach 2:
The sensor pods are designed as universal modules that can measure multiple parameters (light, temperature, humidity, CO2) simultaneously. This multi-functionality reduces the total number of separate devices needed, simplifying the automated system while improving monitoring productivity through comprehensive data collection.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This solution provides cost-effective and efficient monitoring of plant conditions, optimizing growth and reducing the need for manual intervention while ensuring each plant receives maximum light exposure.
Implementation Method 1
a plurality of light sensors configured to measure light received from above the self-propelled sensing system and light received from below the self-propelled sensing system
Data Source
AI summary
A sensing system includes at least one sensor and a movement subsystem configured to move the at least one sensor between a plant and a light source.